ER Stress Response and Induction of Apoptosis in Malignant Pleural Mesothelioma: The Achilles Heel Targeted by the Anticancer Ruthenium Drug BOLD-100.
Elia RanzatoGregorio BonsignoreSimona MartinottiPublished in: Cancers (2022)
Malignant mesothelioma is a rare cancer arising from the serosal surfaces of the body, mainly from the pleural layer. This cancer is strongly related to asbestos exposure and shows a very inauspicious prognosis, because there are scarce therapeutic options for this rare disease. Thus, there is an urgent need to develop novel therapeutic approaches to treat this form of cancer. To explore the biology of malignant pleural mesothelioma (MPM), we previously observed that MPM cell lines show high expression of the GRP78 protein, which is a chaperone protein and the master regulator of the unfolded protein response (UPR) that resides in the endoplasmic reticulum (ER). Based on our previous studies showing the importance of GRP78 in MPM, we observed that BOLD-100, a specific modulator of GRP78 and the UPR, shows cytotoxicity against MPM cells. Our studies demonstrated that BOLD-100 increases ROS production and Ca 2+ release from the ER, leading to ER stress activation and, ultimately, to cell death. Our in vitro data strongly suggest that BOLD-100 inhibits the growth of MPM cell lines, proposing the application as a single agent, or in combination with other standard-of-care drugs, to treat MPM.
Keyphrases
- endoplasmic reticulum
- cell death
- endoplasmic reticulum stress
- papillary thyroid
- cell cycle arrest
- induced apoptosis
- squamous cell
- resting state
- binding protein
- protein protein
- oxidative stress
- emergency department
- palliative care
- lymph node metastasis
- amino acid
- poor prognosis
- estrogen receptor
- cell surface
- dna damage
- small molecule
- case control
- machine learning
- cell proliferation
- drug delivery
- drug induced
- childhood cancer
- escherichia coli
- adverse drug
- cystic fibrosis
- signaling pathway
- quality improvement
- heat stress
- biofilm formation
- data analysis